Designing a Multi-epitope Vaccine against the SARS-CoV-2 Variant based on an Immunoinformatics Approach

  • Authors: Farhani I.1, Yamchi A.2, Madanchi H.3, Khazaei V.1, Behrouzikhah M.4, Abbasi H.1, Salehi M.5, Moradi N.6, Sanami S.7
  • Affiliations:
    1. Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Golestan University of Medical Sciences
    2. Department of Plant Breeding and Biotechnology, Gorgan University of Agricultural Science and Natural Resources
    3. Drug Design and Bioinformatics Unit, Department of Medical Biotechnology,, Biotechnology Research Center, Pasteur Institute of Iran
    4. Department of Medical Microbiology, School of Medicine, Golestan University of Medical Sciences
    5. Department of Medical Genetics, School of Advanced Technologies in Medicine, Golestan University of Medical Sciences
    6. Department of Medical Biotechnology, School of Advanced Technologies in Medicine,, Golestan University of Medical Sciences
    7. Department of Plant Breeding and Biotechnology, Shahrekord University of Medical Sciences
  • Issue: Vol 20, No 3 (2024)
  • Pages: 274-290
  • Section: Chemistry
  • URL: https://j-morphology.com/1573-4099/article/view/643990
  • DOI: https://doi.org/10.2174/1573409919666230612125440
  • ID: 643990

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Full Text

Abstract

Background:SARS-CoV-2 is a life-threatening virus in the world. Scientific evidence indicates that this pathogen will emerge again in the future. Although the current vaccines have a pivotal role in the control of this pathogen, the emergence of new variants has a negative impact on their effectiveness.

Objective:Therefore, it is urgent to consider the protective and safe vaccine against all subcoronavirus species and variants based on the conserved region of the virus. Multi-epitope peptide vaccine (MEV), comprised of immune-dominant epitopes, is designed by immunoinformatic tools and it is a promising strategy against infectious diseases.

Methods:Spike glycoprotein and nucleocapsid proteins from all coronavirus species and variants were aligned and the conserved region was selected. Antigenicity, toxicity, and allergenicity of epitopes were checked by a proper server. To robust the immunity of the multi-epitope vaccine, cholera toxin b (CTB) and three HTL epitopes of tetanus toxin fragment C (TTFrC) were linked at the N-terminal and C-terminal of the construct, respectively. Selected epitopes with MHC molecules and the designed vaccines with Toll-like receptors (TLR-2 and TLR-4) were docked and analyzed. The immunological and physicochemical properties of the designed vaccine were evaluated. The immune responses to the designed vaccine were simulated. Furthermore, molecular dynamic simulations were performed to study the stability and interaction of the MEV-TLRs complexes during simulation time by NAMD (Nanoscale molecular dynamic) software. Finally, the codon of the designed vaccine was optimized according to Saccharomyces boulardii.

Results:The conserved regions of spike glycoprotein and nucleocapsid protein were gathered. Then, safe and antigenic epitopes were selected. The population coverage of the designed vaccine was 74.83%. The instability index indicated that the designed multi-epitope was stable (38.61). The binding affinity of the designed vaccine to TLR2 and TLR4 was -11.4 and -11.1, respectively. The designed vaccine could induce humoral and cellular immunity.

Conclusion:In silico analysis showed that the designed vaccine is a protective multi-epitope vaccine against SARS-CoV-2 variants.

About the authors

Ibrahim Farhani

Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Golestan University of Medical Sciences

Email: info@benthamscience.net

Ahad Yamchi

Department of Plant Breeding and Biotechnology, Gorgan University of Agricultural Science and Natural Resources

Author for correspondence.
Email: info@benthamscience.net

Hamid Madanchi

Drug Design and Bioinformatics Unit, Department of Medical Biotechnology,, Biotechnology Research Center, Pasteur Institute of Iran

Email: info@benthamscience.net

Vahid Khazaei

Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Golestan University of Medical Sciences

Email: info@benthamscience.net

Mehdi Behrouzikhah

Department of Medical Microbiology, School of Medicine, Golestan University of Medical Sciences

Email: info@benthamscience.net

Hamidreza Abbasi

Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Golestan University of Medical Sciences

Email: info@benthamscience.net

Mohammad Salehi

Department of Medical Genetics, School of Advanced Technologies in Medicine, Golestan University of Medical Sciences

Email: info@benthamscience.net

Nilufar Moradi

Department of Medical Biotechnology, School of Advanced Technologies in Medicine,, Golestan University of Medical Sciences

Email: info@benthamscience.net

Samira Sanami

Department of Plant Breeding and Biotechnology, Shahrekord University of Medical Sciences

Email: info@benthamscience.net

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